Apache Flink 是一个分布式流处理框架,用于实时处理无界和有界数据流
以下是使用 Apache Flink 监控 S3 文件夹并处理丢失文件的步骤:
pom.xml
文件中添加以下依赖:<dependencies>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-s3_2.11</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>com.amazonaws</groupId>
<artifactId>aws-java-sdk-s3</artifactId>
<version>${aws.sdk.version}</version>
</dependency>
</dependencies>
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.s3.FlinkS3FileSystem;
import org.apache.flink.streaming.connectors.s3.S3StreamInputFormat;
public class S3Monitor {
public static void main(String[] args) throws Exception {
// 设置 Flink 执行环境
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// 配置 S3 连接参数
env.getConfig().setGlobalJobParameters(new Configuration());
Configuration config = new Configuration();
config.setString("fs.s3a.access.key", "your-access-key");
config.setString("fs.s3a.secret.key", "your-secret-key");
config.setString("fs.s3a.endpoint", "s3.amazonaws.com");
// 创建 S3 数据流
DataStream<String> s3Stream = env.createInput(
new S3StreamInputFormat<>(
new Path("s3://your-bucket/your-folder"),
new SimpleStringSchema()
)
);
// 处理 S3 文件流
s3Stream.map(new MapFunction<String, Tuple2<String, String>>() {
@Override
public Tuple2<String, String> map(String value) throws Exception {
// 解析 S3 文件内容并处理丢失文件
return new Tuple2<>(fileName, fileContent);
}
}).print();
// 执行 Flink 程序
env.execute("S3 Monitor");
}
}
ProcessFunction
来跟踪文件的状态,或者使用 WindowFunction
来对一定时间范围内的文件进行处理。
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